Jian Tang

Jiarui Lu

CoRR, 2024

Structure-Informed Protein Language Model.

[BibT_eX]

[DOI]

Jiarui Lu

CoRR, 2024

The 1st International Workshop on Graph Foundation Models (GFM).

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention.

[BibT_eX]

[DOI]

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Evaluating Representation Learning on the Protein Structure Universe.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards Foundation Models for Knowledge Graph Reasoning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Multi-modal molecule structure-text model for text-based retrieval and editing.

[BibT_eX]

[DOI]

Animashree Anandkumar

Nat. Mac. Intell., December, 2023

Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., May, 2023

Scientific discovery in the age of artificial intelligence.

[BibT_eX]

[DOI]

Nat., 2023

PDB-Struct: A Comprehensive Benchmark for Structure-based Protein Design.

[BibT_eX]

[DOI]

CoRR, 2023

Large Language Models can Learn Rules.

[BibT_eX]

[DOI]

CoRR, 2023

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

[BibT_eX]

[DOI]

CoRR, 2023

GraphText: Graph Reasoning in Text Space.

[BibT_eX]

[DOI]

CoRR, 2023

Evolving Computation Graphs.

[BibT_eX]

[DOI]

Andreea Deac

CoRR, 2023

Score-based Enhanced Sampling for Protein Molecular Dynamics.

[BibT_eX]

[DOI]

Jiarui Lu

Bozitao Zhong

CoRR, 2023

GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow.

[BibT_eX]

[DOI]

CoRR, 2023

Enhancing Protein Language Models with Structure-based Encoder and Pre-training.

[BibT_eX]

[DOI]

CoRR, 2023

A Text-guided Protein Design Framework.

[BibT_eX]

[DOI]

CoRR, 2023

Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction.

[BibT_eX]

[DOI]

CoRR, 2023

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs.

[BibT_eX]

[DOI]

Zhaocheng Zhu

Xinyu Yuan

Michael Galkin

Maxime Gazeau

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials.

[BibT_eX]

[DOI]

Animashree Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GAUCHE: A Library for Gaussian Processes in Chemistry.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Protein Representation Learning by Geometric Structure Pretraining.

[BibT_eX]

[DOI]

Arian Rokkum Jamasb

Proceedings of the Eleventh International Conference on Learning Representations, 2023

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Protein Sequence and Structure Co-Design with Equivariant Translation.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching.

[BibT_eX]

[DOI]

Shengchao Liu

Hongyu Guo

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning on Large-scale Text-attributed Graphs via Variational Inference.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Empirical Study of Retrieval-Enhanced Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Flaky Performances When Pretraining on Relational Databases (Student Abstract).

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Signed Laplacian Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

GAUCHE: A Library for Gaussian Processes in Chemistry.

[BibT_eX]

[DOI]

CoRR, 2022

EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data.

[BibT_eX]

[DOI]

CoRR, 2022

Flaky Performances when Pretraining on Relational Databases.

[BibT_eX]

[DOI]

CoRR, 2022

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking.

[BibT_eX]

[DOI]

CoRR, 2022

Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree.

[BibT_eX]

[DOI]

CoRR, 2022

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

[BibT_eX]

[DOI]

CoRR, 2022

Learning to Efficiently Propagate for Reasoning on Knowledge Graphs.

[BibT_eX]

[DOI]

Zhaocheng Zhu

Xinyu Yuan

Maxime Gazeau

CoRR, 2022

Augmenting Message Passing by Retrieving Similar Graphs.

[BibT_eX]

[DOI]

CoRR, 2022

HIRL: A General Framework for Hierarchical Image Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction.

[BibT_eX]

[DOI]

CoRR, 2022

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version.

[BibT_eX]

[DOI]

CoRR, 2022

TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery.

[BibT_eX]

[DOI]

CoRR, 2022

PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Inductive Logical Query Answering in Knowledge Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction.

[BibT_eX]

[DOI]

Proceedings of the Learning on Graphs Conference, 2022

Neural-Symbolic Models for Logical Queries on Knowledge Graphs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Generative Coarse-Graining of Molecular Conformations.

[BibT_eX]

[DOI]

Rafael Gómez-Bombarelli

Proceedings of the International Conference on Machine Learning, 2022

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Neural Structured Prediction for Inductive Node Classification.

[BibT_eX]

[DOI]

Huiyu Cai

Proceedings of the Tenth International Conference on Learning Representations, 2022

Pre-training Molecular Graph Representation with 3D Geometry.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Structured Multi-task Learning for Molecular Property Prediction.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering.

[BibT_eX]

[DOI]

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation.

[BibT_eX]

[DOI]

Trans. Assoc. Comput. Linguistics, 2021

Utilizing graph machine learning within drug discovery and development.

[BibT_eX]

[DOI]

Briefings Bioinform., 2021

Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction.

[BibT_eX]

[DOI]

Zhaocheng Zhu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Joint Modeling of Visual Objects and Relations for Scene Graph Generation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How to transfer algorithmic reasoning knowledge to learn new algorithms?

[BibT_eX]

[DOI]

Andreea Deac

Petar Velickovic

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Predicting Molecular Conformation via Dynamic Graph Score Matching.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Algorithmic Reasoners are Implicit Planners.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Artificial Intelligence for Drug Discovery.

[BibT_eX]

[DOI]

Fei Wang

Feixiong Cheng

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Unsupervised Path Representation Learning with Curriculum Negative Sampling.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Self-supervised Graph-level Representation Learning with Local and Global Structure.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming.

[BibT_eX]

[DOI]

Rafael Gómez-Bombarelli

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Gradient Fields for Molecular Conformation Generation.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Neural Generative Dynamics for Molecular Conformation Generation.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs.

[BibT_eX]

[DOI]

Junkun Chen

Proceedings of the 9th International Conference on Learning Representations, 2021

Predicting Infectiousness for Proactive Contact Tracing.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

GraphMix: Improved Training of GNNs for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Utilising Graph Machine Learning within Drug Discovery and Development.

[BibT_eX]

[DOI]

CoRR, 2020

Sobolev Wasserstein GAN.

[BibT_eX]

[DOI]

CoRR, 2020

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing.

[BibT_eX]

[DOI]

CoRR, 2020

XLVIN: eXecuted Latent Value Iteration Nets.

[BibT_eX]

[DOI]

CoRR, 2020

Graph neural induction of value iteration.

[BibT_eX]

[DOI]

Andreea Deac

Pierre-Luc Bacon

CoRR, 2020

GRADE: Graph Dynamic Embedding.

[BibT_eX]

[DOI]

Simeon E. Spasov

Alessandro Di Stefano

Pietro Liò

CoRR, 2020

COVI White Paper.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games.

[BibT_eX]

[DOI]

CoRR, 2020

Towards Interpretable Natural Language Understanding with Explanations as Latent Variables.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Graph Policy Network for Transferable Active Learning on Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Dynamic Belief Graphs to Generalize on Text-Based Games.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Continuous Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

A Graph to Graphs Framework for Retrosynthesis Prediction.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs.

[BibT_eX]

[DOI]

Tianyu Gao

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning.

[BibT_eX]

[DOI]

Sai Krishna Gottipati

Proceedings of the 37th International Conference on Machine Learning, 2020

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Deep Geometric Knowledge Distillation with Graphs.

[BibT_eX]

[DOI]

Carlos Lassance

Myriam Bontonou

Ghouthi Boukli Hacene

Vincent Gripon

Antonio Ortega

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Attending Over Triads for Learning Signed Network Embedding.

[BibT_eX]

[DOI]

Shagun Sodhani

Frontiers Big Data, 2019

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation.

[BibT_eX]

[DOI]

CoRR, 2019

GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures.

[BibT_eX]

[DOI]

Jean Michel D. Sellier

CoRR, 2019

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization.

[BibT_eX]

[DOI]

Fan-Yun Sun

Jordan Hoffmann

CoRR, 2019

Weakly-supervised Knowledge Graph Alignment with Adversarial Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Learning Powerful Policies by Using Consistent Dynamics Model.

[BibT_eX]

[DOI]

CoRR, 2019

Drug-Drug Adverse Effect Prediction with Graph Co-Attention.

[BibT_eX]

[DOI]

CoRR, 2019

GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding.

[BibT_eX]

[DOI]

Proceedings of the World Wide Web Conference, 2019

Session-Based Social Recommendation via Dynamic Graph Attention Networks.

[BibT_eX]

[DOI]

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases.

[BibT_eX]

[DOI]

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

vGraph: A Generative Model for Joint Community Detection and Node Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Probabilistic Logic Neural Networks for Reasoning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

GMNN: Graph Markov Neural Networks.

[BibT_eX]

[DOI]

Carlos Eduardo Rosar Kós Lassance

Proceedings of the 36th International Conference on Machine Learning, 2019

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Structural Robustness for Deep Learning Architectures.

[BibT_eX]

[DOI]

Vincent Gripon

Carlos Eduardo Rosar Kós Lassance

Antonio Ortega

Proceedings of the IEEE Data Science Workshop, 2019

Introducing Graph Smoothness Loss for Training Deep Learning Architectures.

[BibT_eX]

[DOI]

Myriam Bontonou

Ghouthi Boukli Hacene

Vincent Gripon

Antonio Ortega

Proceedings of the IEEE Data Science Workshop, 2019

AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

GRLA 2019: The first International Workshop on Graph Representation Learning and its Applications.

[BibT_eX]

[DOI]

Huawei Shen

Peng Bao

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2019, 2019

2018

PixelSNE: Pixel-Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen-Resolution Precision.

[BibT_eX]

[DOI]

Comput. Graph. Forum, 2018

Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Jiawei Han

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

DeepInf: Social Influence Prediction with Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Deriving User Preferences of Mobile Apps from Their Management Activities.

[BibT_eX]

[DOI]

ACM Trans. Inf. Syst., 2017

Roaming across the Castle Tunnels: an Empirical Study of Inter-App Navigation Behaviors of Android Users.

[BibT_eX]

[DOI]

CoRR, 2017

End-to-end Learning for Short Text Expansion.

[BibT_eX]

[DOI]

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

An Attention-based Collaboration Framework for Multi-View Network Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Matching Consumer Health Vocabulary with Professional Medical Terms Through Concept Embedding.

[BibT_eX]

[DOI]

Yue Wang

V. G. Vinod Vydiswaran

Kai Zheng

Hua Xu

Proceedings of the AMIA 2017, 2017

2016

Less is More: Learning Prominent and Diverse Topics for Data Summarization.

[BibT_eX]

[DOI]

CoRR, 2016

Context-aware Natural Language Generation with Recurrent Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2016

Identity-sensitive Word Embedding through Heterogeneous Networks.

[BibT_eX]

[DOI]

CoRR, 2016

Visualization Large-scale and High-dimensional Data.

[BibT_eX]

[DOI]

CoRR, 2016

PixelSNE: Visualizing Fast with Just Enough Precision via Pixel-Aligned Stochastic Neighbor Embedding.

[BibT_eX]

[DOI]

CoRR, 2016

Visualizing Large-scale and High-dimensional Data.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on World Wide Web, 2016

Voting with Their Feet: Inferring User Preferences from App Management Activities.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on World Wide Web, 2016

2015

LINE: Large-scale Information Network Embedding.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on World Wide Web, 2015

PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks.

[BibT_eX]

[DOI]

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

"Look Ma, No Hands!" A Parameter-Free Topic Model.

[BibT_eX]

[DOI]

CoRR, 2014

Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Pre-Trained Multi-View Word Embedding Using Two-Side Neural Network.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

One theme in all views: modeling consensus topics in multiple contexts.

[BibT_eX]

[DOI]

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012

Integrating Temporal Usage Pattern into Personalized Tag Prediction.

[BibT_eX]

[DOI]

Lei Zhang

Proceedings of the Web Technologies and Applications - 14th Asia-Pacific Web Conference, 2012

2011

A trigram hidden Markov model for metadata extraction from heterogeneous references.

[BibT_eX]

[DOI]

Bolanle Adefowoke Ojokoh

Inf. Sci., 2011

Co-Ranking Multiple Entities in a Heterogeneous Network: Integrating Temporal Factor and Users' Bookmarks.

[BibT_eX]

[DOI]

Sheng Feng